Journal of Threatened
Taxa | www.threatenedtaxa.org | 26 February 2024 | 16(2): 24646–24657
ISSN 0974-7907
(Online) | ISSN 0974-7893 (Print)
https://doi.org/10.11609/jott.8799.16.2.24646-24657
#8799 | Received 21 October 2023 | Final received 24 December 2023 |
Finally accepted 10 January 2024
Avifaunal assemblage patterns in Bharathapuzha River Basin, Kerala, India
Pazhayattuparambil Narayanan Anoop Raj 1,
Avadhoot Dilip Velankar 2 &
Padmanabhan Pramod 3
1,3 Salim Ali Centre for Ornithology
and Natural History, South India Centre of Wildlife Institute of India, Anaikatty (Post), Coimbatore, Tamil Nadu 641108, India.
1 Manipal Academy of Higher
Education (MAHE), Madhav Nagar, Manipal, Karnataka 576104, India.
1 Siddharth Foundation, No 26,
Abbas Garden, TVS Nagar, Coimbatore, Tamil Nadu 641025, India.
2 12, Saisanket
CHS, Ganeshwadi, Panchpakhadi,
Thane, Maharashtra 400601, India.
1 anupnarayanan1@gmail.com
(corresponding author), 2 avadhoot.velankar@gmail.com, 3 neosacon@gmail
Editor: H. Byju,
Coimbatore, Tamil Nadu, India. Date of publication: 26 February
2024 (online & print)
Citation: Raj,
P.N.A., A.D. Velankar & P. Pramod (2024). Avifaunal
assemblage patterns in Bharathapuzha River Basin,
Kerala, India. Journal of Threatened Taxa 16(2): 24646–24657. https://doi.org/10.11609/jott.8799.16.2.24646-24657
Copyright: © Raj et al. 2024. Creative Commons Attribution 4.0 International License. JoTT allows
unrestricted use, reproduction, and distribution of this article in any medium
by providing adequate credit to the author(s) and the source of publication.
Funding: Kerala State Biodiversity Board.
Competing interests: The authors declare no competing interests.
Author details: Anoop Raj is a doctoral student of Manipal Academy of Higher Education,
Manipal and affiliated with SACON. He is a researcher in bird ecology with a
wildlife biology science background. He is working
on riverine bird communities of the Western Ghats for his Ph.D. Dr. Avadhoot Dilip Velankar is an independent researcher. His area of specialization is
primatology. Dr. Padmanabhan Pramod is a senior
principal scientist and head of the nature education
programme at SACON. He has 27 years of research experience in the bird
community, biodiversity assessment, and applied ornithology.
Author Contributions: ARPN - Study design, Field surveys, Data analysis and Preparation of
manuscript, PP – Study design, Review, Preparation of
manuscript, ADV – Data analysis, Preparation of manuscript.
Acknowledgements: I acknowledge the Kerala State
Biodiversity Board for the funding through the doctoral fellowship programme.
Also extending gratitude to Mrs. Nila, Mrs.
Sheena, and Mr. Subhash for their constant support in data collection. I thank
Mr. Anoop N.R. for his comments in improving the manuscript.
Abstract: Bharathapuzha, the second largest west-flowing
river in the Western Ghats, originates from the northern and southern parts of
the Palghat gap and debouches into the Arabian Sea at Ponnani.
This river is exposed to high levels of anthropogenic pressures. This study
looks into avifaunal assemblage patterns and the factors influencing the
structure of bird communities in different ecological zones of the Bharathapuzha River Basin. The syntropic
birds and flocking birds contribute variations in the bird community assemblage
in the river basin. For the water-dependent and water-associated birds,
mudflats, water flow, riverside vegetation, and distance from the forest were
found to be the influencing factors in the migratory season. The study also
emphasized the importance of protecting these river-associated habitats for the
conservation of birds.
Keywords: Anthropogenic pressures, bird
community, environmental factors, mudflats, Nila
River, riverine birds, riverside vegetation, water flow, water-associated
birds, water-dependent birds.
Introduction
Bird species respond rapidly to
any changes in the environment (Būhning-Gaese 1997; Waide et al. 1999; Donald et al. 2001; Suárez-Seoane et al. 2002; Benton et al. 2003; McCracken & Tallowin 2004; Batáry et al.
2007). The avian species diversity, richness, and abundance are determined by
various factors such as migration, natality, mortality, and availability of
food and niches (Fitzherbert et al. 2008; Jayapal et
al 2009). Many researchers have attempted to study bird communities in the
different habitats in the Western Ghats (Daniels 1989; Pramod 1995, Karanth et al. 2016) which provided useful information
about the distribution trends. Most of these studies focused on forest
ecosystems in the protected area network. Understanding the pattern of
distribution of birds and their drivers in highly disturbed ecosystems outside
the protected area network is less attempted (Garcia et al. 2010; Anand et al.
2010; Chandran & Vishnudas 2018; Variar et al. 2021).
From the origin to the mouth, the
Bharathapuzha River passes through various landscapes
and topographic conditions. Most ecosystems in the river basin are located
outside the protected area network and are vulnerable to anthropogenic
pressures. Deforestation in the hill region, construction of check dams,
indiscriminate sand mining, the spread of weeds and invasive plants inside the
river channel, expansion of monoculture plantations, encroachment and water
pollution are the major threats to the river (John et al. 2019). In this study,
we attempted to understand the pattern of avifaunal assemblage in the Bharathapuzha river basin which is highly disturbed due to
anthropogenic pressures which destroyed the riverine habitats, water quality,
and natural water flow.
Material
and Methods
Study area
Bharathapuzha is a 6th-order river
(Strahler 1964) having a large extent of production landscape in the basin
(Jacob & Narayanaswami 1954; John et al 2019).
The total area of the river drainage basin is 6186 km2, which
includes 50 watersheds and 290 mini watersheds. Twenty-five percent of the
river drainage basin comes under various protected areas (Raj & Azeez 2010;
John et al. 2019). Silent Valley National Park, one of the important
biodiversity hotspots in the country falls in this river basin. This river
originates from the Thirumurthi hills of Anamalai and flows towards the west through the Palghat Gap
until it drains into the Arabian Sea. Chitturpuzha, Kalpathipuzha, Gayathripuzha, and
Thoothapuzha are major tributaries of this river
which originates from the Western Ghats. These rivers play a crucial role in
maintaining the water flow in the river.
Study design
Field surveys were conducted in
453 km stretches of the river between the elevation gradient of 621–0 m. The
intensive sampling area was selected using stratified sampling techniques. The
area was stratified into three ecological zones based on the river flow,
geomorphology, and ecological setting of the river. Thus, the sampling
locations were classified into the upper reaches (headwaters), middle reaches
(tributary), and lower reaches (main course and estuary) of the river which are
henceforth termed ecological zones (Abell et al. 2008). Considering the extent
of area available in these zones, the sampling locations and sampling efforts
were distributed. Sampling was done in
one non-migratory (April to October 2018) and two migratory seasons (November
2017–February 2018, and November 2018–February 2019). The riverine area in the
basin was gridded into 1 km2 grids. From these, 70 grids along the
river channel were selected through random sampling for intensive study (Figure
1). In each grid, data on birds and associated environmental parameters were
collected through 4-point counts (each 15-minute long) using the fixed width point
count method (Reynolds et al. 1980). Thus, for the three seasons together, a
total of 840-point counts of bird data collection were conducted from the
sampling area. Observations were done 0600–1100 h and 1530–1900 h. Bird
identification was done using field guides and photographs (Ali & Ripley
1983; Ali 1999; Karmierczak 2000; Grimmett
et al. 2014).
Data preparation
Data collected from 70
grids in three seasons (two migratory, one non-migratory) were tabulated and
organized as 210 samples. Contingency tables were created as samples vs.
species with abundance values as scores using the pivot table function in the
spreadsheet package. Samples with no detection were removed from the
tables.
Bird group categories
The bird species recorded during
the study period were classified into three groups as water-dependent birds
(WDB), water-associated birds (WAB), and non-water-associated birds (NWAB).
Water-dependent birds (WDB) are
the birds that use water as their most preferred habitat. This includes the
taxonomic groups such as Anseriformes, Suliformes, and a few members of Charadriiforms.
Water-associated birds (WAB)
include the taxonomic groups such as Pelecaniformes, Ciconiformes, Gruiformes, Charadriiformes, and a few members of Coraciiforms,
Passeriformes, and Accipitriformes.
Non-water-associated birds (NWAB)
are the birds that don’t use riverine habitats as primary habitats. Galliformes, Podicipediformes, Cuculiformes, Caprimulgiformes, Accipitriformes, Strigiformes, Trogoniformes, Bucerotiformes, Coraciiforms, Piciformes, Falconiformes, Psittaciformes,
and Passeriformes come under this category.
Environmental parameters
Data on 17 environmental
parameters were collected. The parameters such as check dams, waste dumping,
and artificial perches were recorded as presence and absence. Area of water
channel, water flow, riverside vegetation, mudflats, sandbanks, rocks and
barren land recorded in percentage (%) in a unit area by visual estimation. The
canopy cover was recorded using the Canopeo (Patrignani et al. 2015). The distance from the nearest
forest, agricultural land, and human settlements was collected on a km scale
using the Google Earth Pro application. The temperature and rainfall data were
collected from the Worldclim database for the study
period.
Analysis
To assess the community structure
and its variation across ecological zones and seasons, non-metric
multidimensional scaling (nMDS) was performed
(Kruskal 1964; Borcard et al. 2011). For nMDS, the contingency table was prepared using one
nonmigratory and migratory season data. Analysis was performed separately for
WDB, WAB, and NWAB. Bray-Curtis dissimilarity index being sensitive to
differences in abundances and does not rely on absences has been used
extensively in community ecology (Schroeder & Jenkins 2018; Lorenzón et al. 2019). Hence, a distance matrix with
Bray-Curtis dissimilarities was used for nMDS
ordination. To determine if the clusters shown in nMDS
ordination are statistically significant, ANOSIM was also performed using the
Bray-Curtis dissimilarity matrix (Anderson & Walsh 2013). ANOSIM was
performed using ecological zone and season as grouping variables.
Similarity Percentage (SIMPER)
analysis was employed to further assess the contribution of the species to the
dissimilarities between the grouping variables (Clarke 1993; White et al. 2005;
Asefa et al. 2017).
To test the impact of
environmental parameters on the community structure of WDB and WAB in migratory
and non-migratory seasons, distance-based redundancy analysis was used
(Legendre & Anderson 1999). First, a global model was performed by
incorporating all non-auto-correlated environmental variables. Linear
dependencies for all environmental variables were checked by computing variance
inflation factors (VIF) for each variable. The variable reduction was performed
using the forward selection method (Boccard et al.
2011) by including variables with VIF below 10. A most parsimonious model was
computed using the environmental variables within α = 0.05 during the forward
selection method. The proportion of variation explained by each variable was
calculated by adjusting the R2 value with the R2 value of
the global model as the threshold.
All statistical analysis was
performed in R statistical language (v4.3.2) with R Studio IDE (v2023.06.0).
Vegan, a community ecology package was used to perform ordination and
significance testing (Oksanen et al. 2013).
Ordination graphs were generated using the package ggplot2 (Wickham 2016).
RESULTS
Bird assemblage patterns across
ecozones and season
The study recorded 235 species of
birds while employing the sampling protocols. There were 23 species of WDB, 49
species of WAB, and 163 NWAB recorded from the river basin.
Water dependent birds
Ordination shows that the
avifaunal community in the middle reaches is not distinct and completely
overlaps within the upper and middle reaches (Figure 2). Some WDBs distinctly
favored sites from either upper or lower reaches (nMDS:
stress = 0.15, non-metric R2 = 0.97). The variation between
ecological zones was more significant than within ecological zones
(ANOSIM: R = 0.132, p <0.05). However, the bird community variation observed
between migratory and non-migratory seasons was not significant (ANOSIM: R = 0.007,
p <0.7).
Little Cormorants Microcarbo niger,
Black-headed Gull Chroicocephalus ridibundus, Brown-headed Gull Chroicocephalus
brunnicephalus, White-breasted Waterhen Amaurornis phoenicurus,
Palla’s Gull Ichthyaetus
ichthyaetus, and Oriental Darter Anhinga
melanogaster contributed to the community variation in the lower and middle
reaches. Along with the above-mentioned bird species, the presence of River
Tern Sterna aurantia and Lesser Whistling Duck
Dendrocygna javanica
contributed to the community variation in the lower and upper reaches. Little
Cormorant, White-breasted Waterhen, River Tern, and Lesser Whistling Duck
contributed to the community variation between the middle and upper reaches.
Water associated birds
The lower reaches and middle reaches
have many sites with similar species composition, however, many sites recorded
very distinct composition (nMDS: Stress = 0.219,
Non-metric R2 = 0.94) (Figure 3). Similarly, several sites in the
middle and lower reaches were similar in composition to the upper reaches.
Also, lower and upper reaches have sites with unique compositions specific to
the respective ecological zones. The variation between ecological zones is more
significant than within ecological zones (ANOSIM: R = 0.159, p <0.05). While
considering the lower reaches and upper reaches separately, the sites with
unique compositions are more. Due to this, species composition between seasons
is significantly different (ANOSIM: R = 0.039, p <0.05).
Cattle Egret Bubulcus
ibis, Brahmini Kite Haliastur
indus, Little Egret Egretta
garzetta, Green Bee-eater Merops
orientalis, Indian Pond Heron Ardeola
grayii, Asian Openbill Anastomus
oscitans contributed maximum to the bird
community variation between lower and middle reaches. A similar pattern was
seen in the lower and upper reaches.
Along with the other bird species White-throated Kingfisher Halcyon smyrnensis also contributed to the variation between
middle and upper reaches. The presence of other species like Red-wattled Lapwing Vanellus
indicus, Black-headed Ibis Threskiornis
melanocephalus, Large Pied Wagtail Motacilla maderaspatensis,
Common Sandpiper Actitis hypoleucos, Intermediate Egret Ardea
intermedia, Chestnut-headed Bee-eater Merops
leschenaulti, and Marsh Sandpiper Tringa stagnatilis had
different abundances between ecological zones which resulted in dissimilarities
evident in nMDS and ANOSIM.
Non-water associated birds
The lower reaches, middle
reaches, and upper reaches are distinct in species compositions (nMDS: Stress = 0.19, Non-metric R2 = 0.96 ) (Figure 4). However, most of the sites in the middle
are similar in composition with upper and lower reaches. Lower and upper
reaches have more unique sites with NWABs than with WDBs and WABs. The
variation between ecological zones is higher than within ecological zones
(ANOSIM: R = 0.154, p <0.05). Some sites have unique seasonal assemblages of
birds. This made composition in the migratory seasons, and seasonal variation
significant (ANOSIM: R = 0.053, p <0.05).
In non-river-associated birds,
differential abundances of synanthropic species were
found to be contributing factors to dissimilarity between ecozones. House Crow Corvus splendens,
Asian Palm Swift Cypsiurus balasiensis, Rock Pigeon Columba livia,
Common Myna Acridotheres tristis, Yellow-billed Babbler Turdoides
affinis, Large-billed Crow Corvus
macrorhynchos and Barn Swallow Hirundo rustica
contributed to the bird community variation between the lower and middle
reaches; middle and upper reaches; and lower and upper reaches. The abundance
variation of Black Kite Milvus migrans and
Purple-rumped Sunbird Leptocoma
zeylonica, also contributed much to these
variations.
Factors Influencing Bird
Community structure in Bharathapuzha river basin
Selected environmental parameters
were analyzed using distance-based redundancy analysis (Db-RDA) for WDBs and
WABs during the migratory season and non-migratory seasons. The results are
given below.
Water-depended birds in migratory
season
Db-RDA for WABs during migratory
season showed that the constrained axis explained the significant variation
(CAP1 Eigenvalue = 1.87 Proportion explained = 78.0%, CAP2 Eigenvalue = 0.52
Proportion explained = 21.9%) (Figure 5). Forward selection of environmental
variables revealed that the Area of mudflats (R2 = 0.048, F = 5.86,
p <0.05), area of water flow (R2 = 0.02, F = 2.82, p <0.05)
and riverside vegetation (R2 = 0.02, F = 3.30, p <0.05) to be
affecting species composition in sites with 9.4% variation explained in Table
1.
Water-depended birds during the
non-migratory season
Db-RDA for WDBs during migratory
season showed no constrained or unconstrained axis explaining significant
variation. Forward selection of environmental variables also didn’t show
significant variation between bird community and environmental variables (Table
2).
Water-associated birds in
Migratory season
Db-RDA for water-associated birds
during migratory explained that the constrained axis showed significant
variation (CAP1 Eigenvalue = 2.51 Proportion explained = 65.1%, CAP2 Eigenvalue
= 0.70, Proportion explained = 18.15%) (Figure 6). Forward selection of
environmental variables revealed that the area of mudflats (R2 =
0.05, F = 8.13, p <0.05) and area of water flow (R2 = 0.02, F =
3.39, p <0.05), distance from forest (R2 = 0.05, F = 8.13, p
<0.05), and distance from farm (R2 = 0.05, F = 8.13, p <0.05)
weakly affected species composition in ecological zones with 9.4% variation
explained in Table 3.
Water-associated birds in
Non-migratory season
Db-RDA for WABs during migratory
season showed that only one constrained axis explained significant variation (CAP1
Eigenvalue = 0.46 Proportion explained = 46.7%, MDS1 Eigenvalue = 3.02
Proportion explained = 13.88%) (Figure 7). Forward selection of environmental
variables revealed that the area of mudflats (R2 = 0.05, F = 8.13, p
<0.05) weakly affects species composition in ecological zones with 3.2%
variation explained in Table 4.
Discussion
Bharathapuzha river basin has 262 species of
birds with a significant number of residents and migrants which are distributed
throughout the basin (Raj et al. 2023). This indicates the diversity of
productive and heterogeneous habitats in the river basin.
This study showed that the bird
species composition varied significantly between the ecological zones. This could be because of
habitat heterogeneity, seasonal movement patterns, population changes,
availability of food and space and climatic conditions in the ecological zones.
Similar observations on bird communities were explained earlier by many (Meyer
& Turner 1992; Namgail et al. 2017; Gonz´alez-Gajardo et al. 2009; Runge et al. 2015; Yang et
al. 2022).
The bird community includes
various species of flocking birds, colonial breeding birds and synanthropic birds. Their contribution to the variation was
more visible due to the relatively high abundance. The high abundance of synanthropic species such as Red-vented Bulbul,
Red-whiskered Bulbul, House Crow, and Black Drongo is
considered as an indicator of human influence or urbanization (Plass & Wunderle 2013: Kurucz et al. 2021). They were found to be in high
abundance in the upper reaches indicating that the habitats in the upper
reaches are under anthropogenic pressure (John et al. 2019). Black Kite, Brahmini Kite, Cattle Egret, Rock Pigeon and House Crow
were found in large numbers in the lower reaches. This indicates that the lower
reaches of the river is highly urbanised
and the generalist species thrive in the region.
The resident birds also
contributed to the changes in the species composition. This could be because of
their tolerance and adaptation to local fragmentation and disturbance (Rendón et al. 2008; Donaldson et al. 2016). Areas in the
lower reaches provide wintering sites for many long-distance migrant birds.
Black-headed Gull, Brown-headed Gull, and Pallas’ Gull were found in high
abundance in the lower reaches. This indicates that these migrant birds are
highly dependent on the large waterbodies of the lower reaches.
Environmental factors influencing
the water-dependent and water-associated birds in the Bharathapuzha
river basin.
The area of mudflats, area of
water flow, riverside vegetation, distance from forest, and distance from
farmland are the environmental parameters that have positively influenced the
WDB and WAB bird communities’ distribution. Various studies indicate the
importance of mudflats and the area of water flow on the WAB communities (Bellio & Kingsford 2013; Aarif
et al. 2014; Clemens et al. 2014; Murray & Fuller 2015; Luo et al. 2019).
Mudflats are one of the important
ecosystems which determine the characteristics of the river channel. In the Bharathapuzha river basin, from the upper reaches to the
lower reaches, mudflats are seen everywhere in various degrees. In some
locations, mudflats form due to the natural flow of water, whereas in some
areas it is created due to the check dams. In the upper and lower reaches,
relatively more extensive mudflats are available for the WDB and WAB for
foraging and resting. These mud flats are one of the most productive ecosystems
and are reported to have high levels of benthic and soil biota (Dittmann 2008; Dissanayake 2019). The mud flats in the
river basin are prone to high anthropogenic threats due to encroachment and
sand mining. River-side farming is a common practice in the Bharathapuzha
river basin. The farmers here use these mudflats for farming during the
summers. This extensively reduces the space and food availability of birds.
Destruction or disappearance of these habitats can decrease the diversity of
WDB and WAB. The study strongly recommends the protection and management of
existing mudflats in the riverine area.
The area of water flow represents
the percentage of water in the river channel. Bharathapuzha
is a perennial river. The water level reduces drastically during the summers.
Though the water is less in the river channel, the flow is continuous. The
anthropogenic activities in the river have drastically interrupted the water
flow. The construction of dams and check dams in various places has altered the
natural flow. The large waders (herons, egrets, and storks) and shorebirds
(plovers and sandpipers) prefer the shallow flowing water in the lower reaches.
But the deep divers like kingfishers are seen mostly in the middle reaches. The
ducks and cormorants prefer the stagnant water in the dams and check dams. This
indicates that the changes in the water levels in the river channel influence
the bird community. The study highlights the importance of maintaining the flow
of the river to protect the birds and ecosystem in the river basin.
Riverside vegetation includes the
vegetation patches seen on the riverside, inside the river channel, and the
floating vegetation on the water. The egrets and herons are seen foraging in
these habitats. The White-breasted Waterhen and Purple Moorhen were found
nesting on floating vegetation. In many locations, the vegetation inside the
water channel was created due to anthropogenic activities such as sand mining
and check dam construction. Several bird species use this as a breeding and
foraging ground. Large flocks of Cattle Egrets and little cormorants are seen
in such vegetation. Apart from the birds, otters also are observed to use this
area as their shelter which is prone to periodical fires in summer.
Distance from forest and distance
from farmland shows a weak statistical significance in its effect on the bird
communities. The lower reaches of the Bharathapuzha
River are dominated by paddy cultivation. Most of the WAB depend on these
habitats for foraging.
Conclusion
The present
study, recommends a
systematic survey of the check dams and their effectiveness in the river basin.
A regulation on check dam construction has to be brought into action and
unwanted check dams should be removed to ensure the water flow. No significant
correlations between most variables and birds were found in our study in the
non-migratory season. The non-migratory season data collection was conducted
from April 2018 to September 2018, in which the Kerala flood occurred. The
flood in the Bharathapuzha River affected largely on
the microhabitats and riverine ecosystems which in turn reflected on the
environmental parameters collected during the survey. The recent trend in
changes in rainfall patterns, floods and droughts in the river basin may affect
the bird communities. Seasonal variation in river channels and resource availability
needs to be studied in detail. In the present study, most of the study
locations fell outside the protected area network. The bird diversity in the
river basin shows the importance of the non-protected areas in biodiversity
conservation (Raman & Sukumar 2002; Raman & Mudappa
2003; Raman 2006; Anand 2010; Raj et al. 2023). To protect these habitats which
support bird diversity new strategies such as land-sharing with local
communities are required which ensure effective biodiversity conservation over a
large landscape like the Bharathapuzha river basin.
Table 1. Forward selection of
variables and adjusted R2 for distance-based redundancy analysis (db-RDA) of water-dependent birds in the migratory season.
|
|
Variables |
R2 |
R2Cum |
AdjR2Cum |
F |
p value |
|
1 |
Mudflats |
0.048893593 |
0.04889359 |
0.04055055 |
5.8604059 |
0.016* |
|
2 |
Water flow |
0.023191219 |
0.07208481 |
0.05566153 |
2.8241889 |
0.047* |
|
3 |
Check dams |
0.011114354 |
0.08319917 |
0.05864200 |
1.3577732 |
0.251 |
|
4 |
Altitude |
0.011698160 |
0.09489733 |
0.06228101 |
1.4346392 |
0.209 |
|
5 |
Farmland |
0.009676843 |
0.10457417 |
0.06387300 |
1.1887671 |
0.287 |
|
6 |
Barren land |
0.017266246 |
0.12184042 |
0.07350136 |
2.1431422 |
0.100 |
|
7 |
Riverside vegetation |
0.026095423 |
0.14793584 |
0.09270946 |
3.3076214 |
0.039* |
|
8 |
Sandbank |
0.010357548 |
0.15829339 |
0.09536205 |
1.3166793 |
0.247 |
|
9 |
Temperature |
0.006612920 |
0.16490631 |
0.09400213 |
0.8393903 |
0.391 |
|
10 |
Area of water channel |
0.005256994 |
0.17016330 |
0.09113123 |
0.6651722 |
0.530 |
|
11 |
Distance from forest |
0.004208018 |
0.17437132 |
0.08704521 |
0.5300614 |
0.660 |
|
12 |
Rocks |
0.003517995 |
0.17788931 |
0.08210943 |
0.4407600 |
0.641 |
|
13 |
Waste dumping |
0.003243874 |
0.18113319 |
0.07676781 |
0.4040647 |
0.646 |
|
14 |
Rainfall |
0.003320936 |
0.18445412 |
0.07140816 |
0.4112761 |
0.740 |
|
15 |
Perches |
0.002203425 |
0.18665755 |
0.06465618 |
0.2709098 |
0.863 |
|
16 |
Distance from human settlements
|
0.002033782 |
0.18869133 |
0.05757074 |
0.2481724 |
0.776 |
Table 2. Forward selection of
variables and adjusted R2 for distance-based redundancy analysis (db-RDA) of water-dependent birds in the non-migratory
season.
|
|
Variables |
R2 |
R2Cum |
AdjR2Cum |
F |
p value |
|
1 |
Altitude |
0.04512 |
0.04512 |
0.02744 |
2.55158 |
0.072 |
|
2 |
Area of Water channel |
0.03282 |
0.07794 |
0.04314 |
1.88627 |
0.172 |
|
3 |
Distance from forest |
0.04089 |
0.11883 |
0.06799 |
2.4132 |
0.107 |
|
4 |
Temperature |
0.03344 |
0.15227 |
0.08578 |
2.01166 |
0.108 |
|
5 |
Water flow |
0.01454 |
0.16681 |
0.08349 |
0.87254 |
0.353 |
|
6 |
Farmland |
0.0166 |
0.18341 |
0.08342 |
0.99612 |
0.315 |
|
7 |
Riverside vegetation |
0.01542 |
0.19882 |
0.08198 |
0.92355 |
0.356 |
|
8 |
Check dam |
0.01229 |
0.21111 |
0.07683 |
0.73204 |
0.459 |
|
9 |
Barren land |
0.00748 |
0.21859 |
0.0657 |
0.44006 |
0.572 |
|
10 |
Mudflats |
0.00529 |
0.22388 |
0.0514 |
0.30674 |
0.679 |
|
11 |
Sandbanks |
0.00452 |
0.2284 |
0.0355 |
0.25777 |
0.709 |
|
12 |
Distance from human settlement |
0.00437 |
0.23276 |
0.01865 |
0.24464 |
0.64 |
|
13 |
Sewage |
0.003 |
0.23576 |
-0.0008 |
0.16473 |
0.75 |
|
14 |
Waste dumping |
0.00221 |
0.23796 |
-0.0222 |
0.1187 |
0.846 |
|
15 |
Rain fall |
0.0026 |
0.24057 |
-0.0442 |
0.13703 |
0.855 |
|
16 |
Rocks |
0.00106 |
0.24163 |
-0.0695 |
0.05473 |
0.967 |
Table 3. Forward selection of
variables and adjusted R2 for distance-based redundancy analysis (db-RDA) of water-associated birds in the migratory season.
|
|
Variables |
R2 |
R2Cum |
AdjR2Cum |
F |
p value |
|
1 |
Mudflats |
0.04575 |
0.04575 |
0.03873 |
6.52025 |
0.006* |
|
2 |
Water flow |
0.03512 |
0.08087 |
0.06725 |
5.15865 |
0.003* |
|
3 |
Distance from forest |
0.01891 |
0.09978 |
0.07963 |
2.81522 |
0.029* |
|
4 |
Farmland |
0.0182 |
0.11798 |
0.09145 |
2.74392 |
0.033* |
|
5 |
Temperature |
0.00924 |
0.12723 |
0.09417 |
1.39808 |
0.2 |
|
6 |
Riverside vegetation |
0.00831 |
0.13553 |
0.09594 |
1.2586 |
0.234 |
|
7 |
Rainfall |
0.01154 |
0.14707 |
0.10114 |
1.75851 |
0.123 |
|
8 |
Distance from human settlement |
0.01035 |
0.15742 |
0.10516 |
1.58428 |
0.166 |
|
9 |
Perch |
0.00667 |
0.16409 |
0.10531 |
1.02164 |
0.355 |
|
10 |
Altitude |
0.00599 |
0.17008 |
0.10473 |
0.91724 |
0.379 |
|
11 |
Barren land |
0.00499 |
0.17508 |
0.10306 |
0.76294 |
0.504 |
|
12 |
Waste dumping |
0.00372 |
0.1788 |
0.09996 |
0.56611 |
0.644 |
|
13 |
Area of Water channel |
0.00345 |
0.18224 |
0.09651 |
0.52276 |
0.675 |
|
14 |
Sewage |
0.0035 |
0.18574 |
0.09306 |
0.52864 |
0.64 |
|
15 |
Check dam |
0.00285 |
0.18859 |
0.08882 |
0.42777 |
0.829 |
|
16 |
Sandbanks |
0.00258 |
0.19117 |
0.08422 |
0.38617 |
0.818 |
|
17 |
Rocks |
0.00119 |
0.19236 |
0.07794 |
0.17628 |
0.981 |
Table 4. Forward selection of
variables and adjusted R2 for distance-based redundancy analysis (db-RDA) of river-associated birds in non-migratory season.
|
|
variables |
R2 |
R2Cum |
AdjR2Cum |
F |
p value |
|
1 |
Mudflats |
0.04636 |
0.04636 |
0.03192 |
3.20881 |
0.026* |
|
2 |
Sandbanks |
0.03052 |
0.07688 |
0.04848 |
2.14872 |
0.09 |
|
3 |
Riverside vegetation |
0.02782 |
0.1047 |
0.06274 |
1.98887 |
0.091 |
|
4 |
Rock |
0.0219 |
0.1266 |
0.07115 |
1.57952 |
0.168 |
|
5 |
Water flow |
0.01709 |
0.14369 |
0.07463 |
1.23718 |
0.276 |
|
6 |
Barren land |
0.02022 |
0.16391 |
0.08167 |
1.47528 |
0.177 |
|
7 |
Distance from human settlement |
0.01327 |
0.17718 |
0.08118 |
0.9675 |
0.243 |
|
8 |
Distance from forest |
0.01141 |
0.18859 |
0.07857 |
0.82981 |
0.537 |
|
9 |
Check dam |
0.01118 |
0.19977 |
0.07559 |
0.81019 |
0.538 |
|
10 |
Perch |
0.01081 |
0.21058 |
0.07209 |
0.7808 |
0.495 |
|
11 |
Rainfall |
0.00853 |
0.21911 |
0.06573 |
0.61199 |
0.68 |
|
12 |
Area of water channel |
0.00867 |
0.22778 |
0.0593 |
0.61734 |
0.671 |
|
13 |
Temperature |
0.00585 |
0.23363 |
0.04913 |
0.41207 |
0.797 |
|
14 |
Farmland |
0.00597 |
0.2396 |
0.03874 |
0.41588 |
0.828 |
|
15 |
Waste dumping |
0.00795 |
0.24754 |
0.03049 |
0.54923 |
0.685 |
|
16 |
Sewage |
0.00417 |
0.25171 |
0.01695 |
0.28391 |
0.892 |
|
17 |
Altitude |
0.00223 |
0.25394 |
0.00028 |
0.1495 |
0.978 |
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